HBase Architecture: Use Cases, Components & Data Model

HBase Architecture and its Important Components

Below is a detailed architrecutre of HBase with components:

HBase architecture consists mainly of four components

• HMaster
• HRegionserver
• HRegions
• Zookeeper
• HDFS

In this tutorial- you will learn,

• HBase Architecture and its Important Components
• HMaster
• H Region Server
• HRegions
• ZooKeeper
• HDFS
• HBase Data Model
• HBase Use Cases
• Storage Mechanism in HBase
• HBase Read and Write Data Explained
• HBASE vs. HDFS

The following are important roles performed by HMaster in HBase.

• Plays a vital role in terms of performance and maintaining nodes in the cluster.
• HMaster provides admin performance and distributes services to different region servers.
• HMaster assigns regions to region servers.
• HMaster has the features like controlling load balancing and failover to handle the load over nodes present in the cluster.
• When a client wants to change any schema and to change any Metadata operations, HMaster takes responsibility for these operations.

Some of the methods exposed by HMaster Interface are primarily Metadata oriented methods.

• Table (createTable, removeTable, enable, disable)
• ColumnFamily (add Column, modify Column)
• Region (move, assign)

The client communicates in a bi-directional way with both HMaster and ZooKeeper. For read and write operations, it directly contacts with HRegion servers. HMaster assigns regions to region servers and in turn, check the health status of region servers.

In entire architecture, we have multiple region servers. Hlog present in region servers which are going to store all the log files.

HBase Region Servers

When HBase Region Server receives writes and read requests from the client, it assigns the request to a specific region, where the actual column family resides. However, the client can directly contact with HRegion servers, there is no need of HMaster mandatory permission to the client regarding communication with HRegion servers. The client requires HMaster help when operations related to metadata and schema changes are required.

HRegionServer is the Region Server implementation. It is responsible for serving and managing regions or data that is present in a distributed cluster. The region servers run on Data Nodes present in the Hadoop cluster.

HMaster can get into contact with multiple HRegion servers and performs the following functions.

• Hosting and managing regions
• Splitting regions automatically
• Handling read and writes requests
• Communicating with the client directly

HBase Regions

HRegions are the basic building elements of HBase cluster that consists of the distribution of tables and are comprised of Column families. It contains multiple stores, one for each column family. It consists of mainly two components, which are Memstore and Hfile.

ZooKeeper

HBase Zookeeper is a centralized monitoring server which maintains configuration information and provides distributed synchronization. Distributed synchronization is to access the distributed applications running across the cluster with the responsibility of providing coordination services between nodes. If the client wants to communicate with regions, the server’s client has to approach ZooKeeper first.

It is an open source project, and it provides so many important services.

Services provided by ZooKeeper

• Maintains Configuration information
• Provides distributed synchronization
• Client Communication establishment with region servers
• Provides ephemeral nodes for which represent different region servers
• Master servers usability of ephemeral nodes for discovering available servers in the cluster
• To track server failure and network partitions

Master and HBase slave nodes ( region servers) registered themselves with ZooKeeper. The client needs access to ZK(zookeeper) quorum configuration to connect with master and region servers.

During a failure of nodes that present in HBase cluster, ZKquoram will trigger error messages, and it starts to repair the failed nodes.

HDFS

HDFS is a Hadoop distributed File System, as the name implies it provides a distributed environment for the storage and it is a file system designed in a way to run on commodity hardware. It stores each file in multiple blocks and to maintain fault tolerance, the blocks are replicated across a Hadoop cluster.

HDFS provides a high degree of fault –tolerance and runs on cheap commodity hardware. By adding nodes to the cluster and performing processing & storing by using the cheap commodity hardware, it will give the client better results as compared to the existing one.

In here, the data stored in each block replicates into 3 nodes any in a case when any node goes down there will be no loss of data, it will have a proper backup recovery mechanism.

HDFS get in contact with the HBase components and stores a large amount of data in a distributed manner.

HBase Data Model

HBase Data Model is a set of components that consists of Tables, Rows, Column families, Cells, Columns, and Versions. HBase tables contain column families and rows with elements defined as Primary keys. A column in HBase data model table represents attributes to the objects.

HBase Data Model consists of following elements,

• Set of tables
• Each table with column families and rows
• Each table must have an element defined as Primary Key.
• Row key acts as a Primary key in HBase.
• Any access to HBase tables uses this Primary Key
• Each column present in HBase denotes attribute corresponding to object

HBase Use Cases

Following are examples of HBase use cases with a detailed explanation of the solution it provides to various technical problems

HBase Read and Write Data Explained

The Read and Write operations from Client into Hfile can be shown in below diagram.

Step 1) Client wants to write data and in turn first communicates with Regions server and then regions

Step 2) Regions contacting memstore for storing associated with the column family

Step 3) First data stores into Memstore, where the data is sorted and after that, it flushes into HFile. The main reason for using Memstore is to store data in a Distributed file system based on Row Key. Memstore will be placed in Region server main memory while HFiles are written into HDFS.

Step 4) Client wants to read data from Regions

Step 5) In turn Client can have direct access to Mem store, and it can request for data.

Step 6) Client approaches HFiles to get the data. The data are fetched and retrieved by the Client.

Memstore holds in-memory modifications to the store. The hierarchy of objects in HBase Regions is as shown from top to bottom in below table.